Comprehensive in silico discovery of c-Src tyrosine kinase inhibitors in cancer treatment: A unified approach combining pharmacophore modeling, 3D QSAR, DFT, and molecular dynamics simulation
Objective: To investigate c-Src, a non-receptor tyrosine kinase dysregulated in various cancer types including colon, breast, and pancreatic cancers, as a potential drug target for cancer therapy. Methods: Ligand-based pharmacophore modeling and 3D-QSAR analysis on a dataset of 34c-Src tyrosine kina...
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| Format: | Article |
| Language: | English |
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Elsevier
2024-03-01
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| Series: | Journal of King Saud University: Science |
| Subjects: | |
| Online Access: | http://www.sciencedirect.com/science/article/pii/S1018364723005384 |
| _version_ | 1797319469349994496 |
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| author | Saida Khamouli Md. Tabish Rehman Nadjiba Zegheb Afzal Hussain Meraj A. Khan |
| author_facet | Saida Khamouli Md. Tabish Rehman Nadjiba Zegheb Afzal Hussain Meraj A. Khan |
| author_sort | Saida Khamouli |
| collection | DOAJ |
| description | Objective: To investigate c-Src, a non-receptor tyrosine kinase dysregulated in various cancer types including colon, breast, and pancreatic cancers, as a potential drug target for cancer therapy. Methods: Ligand-based pharmacophore modeling and 3D-QSAR analysis on a dataset of 34c-Src tyrosine kinase inhibitors were employed. The established pharmacophore model (DDRRR_1) features two hydrogen bond donor (D) and three aromatic ring (R) features, exhibiting favorable parameters (R2 = 0.926; Q2 = 0.895; F value = 47.9). Hypothesis validation, enrichment analysis, and contour plot analysis were conducted, followed by virtual screening of a PubChem database using the optimized pharmacophore model and filtering based on the Lipinski rule of five. Results: The most promising inhibitors underwent multistep molecular docking, density Functional Theory (DFT) analysis, ADMET assessments, molecular dynamics simulation, and PCA. CID_70144047 emerged as the most promising hit with all the above favorable properties. Conclusion: The study provides a comprehensive approach for identifying novel c-Src tyrosine kinase inhibitors, highlighting CID_70144047 as a promising leads with potential therapeutic applications in cancer treatment. |
| first_indexed | 2024-03-08T04:07:19Z |
| format | Article |
| id | doaj.art-2b2a586f11694b8ba4f8c0a5849afb74 |
| institution | Directory Open Access Journal |
| issn | 1018-3647 |
| language | English |
| last_indexed | 2024-03-08T04:07:19Z |
| publishDate | 2024-03-01 |
| publisher | Elsevier |
| record_format | Article |
| series | Journal of King Saud University: Science |
| spelling | doaj.art-2b2a586f11694b8ba4f8c0a5849afb742024-02-09T04:47:35ZengElsevierJournal of King Saud University: Science1018-36472024-03-01363103076Comprehensive in silico discovery of c-Src tyrosine kinase inhibitors in cancer treatment: A unified approach combining pharmacophore modeling, 3D QSAR, DFT, and molecular dynamics simulationSaida Khamouli0Md. Tabish Rehman1Nadjiba Zegheb2Afzal Hussain3Meraj A. Khan4Group of Computational and Pharmaceutical Chemistry, LMCE Laboratory, University of Biskra, BP 145 Biskra, 07000, Algeria; Corresponding authors.Department of Pharmacognosy, College of Pharmacy, King Saud University, Riyadh 11451, Saudi Arabia; Corresponding authors.VTRS Laboratory, University of El Oued B.P.789, 39000 El Oued, AlgeriaDepartment of Pharmacognosy, College of Pharmacy, King Saud University, Riyadh 11451, Saudi ArabiaProgram in Translational Medicine, Peter Gilgan Centre for Research and Learning, The Hospital for Sick Children, Toronto, Ontario M5G 0A4, Canada; DigiBiomics Inc., Ontario L5M 6W5, CanadaObjective: To investigate c-Src, a non-receptor tyrosine kinase dysregulated in various cancer types including colon, breast, and pancreatic cancers, as a potential drug target for cancer therapy. Methods: Ligand-based pharmacophore modeling and 3D-QSAR analysis on a dataset of 34c-Src tyrosine kinase inhibitors were employed. The established pharmacophore model (DDRRR_1) features two hydrogen bond donor (D) and three aromatic ring (R) features, exhibiting favorable parameters (R2 = 0.926; Q2 = 0.895; F value = 47.9). Hypothesis validation, enrichment analysis, and contour plot analysis were conducted, followed by virtual screening of a PubChem database using the optimized pharmacophore model and filtering based on the Lipinski rule of five. Results: The most promising inhibitors underwent multistep molecular docking, density Functional Theory (DFT) analysis, ADMET assessments, molecular dynamics simulation, and PCA. CID_70144047 emerged as the most promising hit with all the above favorable properties. Conclusion: The study provides a comprehensive approach for identifying novel c-Src tyrosine kinase inhibitors, highlighting CID_70144047 as a promising leads with potential therapeutic applications in cancer treatment.http://www.sciencedirect.com/science/article/pii/S1018364723005384c-Src tyrosine kinasePharmacophore modelingVirtual screeningDrug discoveryDFT analysisMolecular dynamics simulation |
| spellingShingle | Saida Khamouli Md. Tabish Rehman Nadjiba Zegheb Afzal Hussain Meraj A. Khan Comprehensive in silico discovery of c-Src tyrosine kinase inhibitors in cancer treatment: A unified approach combining pharmacophore modeling, 3D QSAR, DFT, and molecular dynamics simulation Journal of King Saud University: Science c-Src tyrosine kinase Pharmacophore modeling Virtual screening Drug discovery DFT analysis Molecular dynamics simulation |
| title | Comprehensive in silico discovery of c-Src tyrosine kinase inhibitors in cancer treatment: A unified approach combining pharmacophore modeling, 3D QSAR, DFT, and molecular dynamics simulation |
| title_full | Comprehensive in silico discovery of c-Src tyrosine kinase inhibitors in cancer treatment: A unified approach combining pharmacophore modeling, 3D QSAR, DFT, and molecular dynamics simulation |
| title_fullStr | Comprehensive in silico discovery of c-Src tyrosine kinase inhibitors in cancer treatment: A unified approach combining pharmacophore modeling, 3D QSAR, DFT, and molecular dynamics simulation |
| title_full_unstemmed | Comprehensive in silico discovery of c-Src tyrosine kinase inhibitors in cancer treatment: A unified approach combining pharmacophore modeling, 3D QSAR, DFT, and molecular dynamics simulation |
| title_short | Comprehensive in silico discovery of c-Src tyrosine kinase inhibitors in cancer treatment: A unified approach combining pharmacophore modeling, 3D QSAR, DFT, and molecular dynamics simulation |
| title_sort | comprehensive in silico discovery of c src tyrosine kinase inhibitors in cancer treatment a unified approach combining pharmacophore modeling 3d qsar dft and molecular dynamics simulation |
| topic | c-Src tyrosine kinase Pharmacophore modeling Virtual screening Drug discovery DFT analysis Molecular dynamics simulation |
| url | http://www.sciencedirect.com/science/article/pii/S1018364723005384 |
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